코골이용 압전센서를 이용한 수면무호흡 검출에 관한 예비 연구
Sleep Apnea Detection Using a Piezo Snoring Sensor: A Pilot study
1
조회
0
다운로드
1
인용
0
참고문헌
키워드
초록
This paper proposed a method that can automatically classify sleep apnea by using features extracted frompulse rate variability(PRV) signals induced from piezo snoring sensor for patients with obstructive sleep apnea(OSA). We have extracted eight features(NN, SDNN, RMSSD, NN10, NN50, LF, HF and LF/HF ratio) based on time andfrequency analyses of PRV. Sleep apnea was classified by a linear discriminant analysis(LDA). A performance wasevaluated using snore recordings from 13 patients with OSA (ages: 54.5 ± 10.5 years, body mass index: 26.3 ± 2.5kg/m2, apnea-hypopnea index: 19.2 ± 6.0/h). The sensitivity and specificity were 78.9 ± 0.9% and 78.9 ± 0.9% fortraining set and 77.7 ± 10.9% and 79.0 ± 2.8% for test set, respectively. Our study demonstrated the feasibility ofimplementing a piezo snoring sensor based on a portable device as a simple and cost-effective solution for contributingto the OSA screening.
Abstract
This paper proposed a method that can automatically classify sleep apnea by using features extracted frompulse rate variability(PRV) signals induced from piezo snoring sensor for patients with obstructive sleep apnea(OSA). We have extracted eight features(NN, SDNN, RMSSD, NN10, NN50, LF, HF and LF/HF ratio) based on time andfrequency analyses of PRV. Sleep apnea was classified by a linear discriminant analysis(LDA). A performance wasevaluated using snore recordings from 13 patients with OSA (ages: 54.5 ± 10.5 years, body mass index: 26.3 ± 2.5kg/m2, apnea-hypopnea index: 19.2 ± 6.0/h). The sensitivity and specificity were 78.9 ± 0.9% and 78.9 ± 0.9% fortraining set and 77.7 ± 10.9% and 79.0 ± 2.8% for test set, respectively. Our study demonstrated the feasibility ofimplementing a piezo snoring sensor based on a portable device as a simple and cost-effective solution for contributingto the OSA screening.
참고문헌 (22)
- C. Iber, "The AASM manual for the scoring of sleep and associated events: rules, terminology and technical specifications" (2007), American Academy of Sleep Medicine
- A. N. Vgontzas., "Sleep apnea and daytime sleepiness and fatigue : relations with visceral obesity, insulin resistance, and hypercytokinemia", J. Clin. Endocrinol. Metab, 85(3), pp.1151~1158 (2000)
- F. Barb., "Automobile accidents in patients with sleep apnea syndrome : An epidemiological and mechanistic study", Am. J. Respir. Crit. Care. Med, 158(1), pp.18~22 (1998)
- R. Bhattacharjee., "Cardiovascular complications of obstructive sleep apnea syndrome : Evidence from children", Prog. Cardiovasc. Dis, 51(5), pp.416~433 (2009)
- F. Roche., "Screening of obstructive sleep apnea syndrome by heart rate variability analysis", Circulation, 100(13), pp.1411~1415 (1999)
- P. K. Stein., "Heart rate variability, sleep and sleep disorders", Sleep Med. Rev, 16(1), pp.47~66 (2012)
- M. O. Mendez., "Automatic screening of obstructive sleep apnea from the ECG based on empirical mode decomposition and wavelet analysis", Physiol. Meas, 31(3), pp.273~289 (2010)
- M. K. Erman., "Validation of the ApneaLinkTM‚ for the screening of sleep apnea : a novel and simple single-channel recording device", J. Clin. Sleep. Med, 3(4), pp.387~392 (2007)
- P. Levy., "Accuracy of oximetry for detection of respiratory disturbances in sleep apnea syndrome", Chest, 109(2), pp.395~399 (1996)
- H. Nakano., "Validation of a new system of tracheal sound analysis for the diagnosis of sleep apnea-hypopnea syndrome", Sleep, 27(5), pp.951~958 (2004)
- 이정훈, "추정된 일회심박출량을 이용한 수면 무호흡 검출", 의공학회지, 34(2), pp.97~103 (2013), 대한의용생체공학회[DOI]
- 박종욱, "광용적맥파 신호를 이용한 수면 중 호흡 추정", 의공학회지, 34(3), pp.105~110 (2013), 대한의용생체공학회[DOI]
- D. S. Morillo., "An accelerometer-based device for sleep apnea screening", IEEE Trans. Inf. Technol. Biomed, 14(2), pp.491~499 (2010)
- C. Doukas., "Automated sleep breath disorders detection utilizing patient sound analysis", Biomed. Signal Process. Control, 7(3), pp.256~264 (2012)
- 이경중, "Snoring detection using a piezo snoring sensor based on hidden Markov models", PHYSIOLOGICAL MEASUREMENT, 34(5), pp.41~49 (2013), IOP PUBLISHING LTD
- 윤자웅, "Improvement of Dynamic Respiration Monitoring Through Sensor Fusion of Accelerometer and Gyro-sensor", Journal of Electrical Engineering & Technology, 9(1), pp.334~343 (2014), 대한전기학회
- Y. Okada., "Wearable ECG recorder with acceleration sensors for monitoring daily stress : Office work simulation study", in Proc. 35th Annual International Conference of the IEEE EMBS, Osaka, Japan, pp.4718~4721 (2013)
- D. B. Rendon., "Mapping the human body for vibrations using an accelerometer", in Proc. 29th Annual International Conference of the IEEE EMBS, Lyon, France, pp.1671~1674 (2007)
- D. S. Morillo., "Monitoring and analysis of cardio respiratory and snoring signals by using an accelerometer", in Proc. 29th Annual International Conference of the IEEE EMBS, Lyon, France, pp.3942~3945 (2007)
- R. A. Dunne, "A Statistical Approach to Neural Networks for Pattern Recognition", pp.19~34 (2007), John Wiley & Sons
- K. Narkiewicz., "Sympathetic activity in obese subjects with and without obstructive sleep apnea", Circulation, 98(8), pp.772~776 (1998)
- M. O. Mendez., "Detection of sleep apnea from surface ECG based on features extracted by an autoregressive model", in Proc. 29th Annual International Conference of the IEEE EMBS, Lyon, France, pp.6105~6108 (2007)